Triple

T12042164
Position Surface form Disambiguated ID Type / Status
Subject Tachov District E286688 entity
Predicate contains P35 FINISHED
Object Planá E286685 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Planá | Statement: [Tachov District, contains, Planá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Planá
Context triple: [Tachov District, contains, Planá]
  • A. Planá chosen
    Planá is a town in the Plzeň Region of the Czech Republic that serves as a local administrative and service center for surrounding municipalities.
  • B. Celestún
    Celestún is a small coastal town in the Mexican state of Yucatán, known for its beaches, fishing community, and as a gateway to nearby flamingo-filled wetlands and nature reserves.
  • C. Marsi
    The Marsi were an ancient Italic tribe of central Italy, known for their role in the Social War against Rome and their association with the worship of the god Mars.
  • D. Gaià
    Gaià is a small rural municipality in the comarca of Bages in Catalonia, Spain.
  • E. Erdek
    Erdek is a coastal town and popular seaside resort in Turkey’s Balıkesir Province, located on the Kapıdağ Peninsula along the Sea of Marmara.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040d13108190bd1a969fa62aae5a completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49da728ec819080c349fd8d0ed62c completed May 1, 2026, 12:33 p.m.
Created at: April 8, 2026, 9:47 p.m.